cifar.py

##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
## Created by: Hang Zhang
## ECE Department, Rutgers University
## Email: zhang.hang@rutgers.edu
## Copyright (c) 2017
##
## This source code is licensed under the MIT-style license found in the
## LICENSE file in the root directory of this source tree 
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

import torch
import torchvision
import torchvision.transforms as transforms

class Dataloder():
	def __init__(self, args):
		transform_train = transforms.Compose([
    	transforms.RandomCrop(32, padding=4),
    	transforms.RandomHorizontalFlip(),
    	transforms.ToTensor(),
    	transforms.Normalize((0.4914, 0.4822, 0.4465), 
				(0.2023, 0.1994, 0.2010)),
		])
		transform_test = transforms.Compose([
    	transforms.ToTensor(),
    	transforms.Normalize((0.4914, 0.4822, 0.4465), 
				(0.2023, 0.1994, 0.2010)),
		])

		trainset = torchvision.datasets.CIFAR10(root='./data', train=True, 
			download=True, transform=transform_train)
		testset = torchvision.datasets.CIFAR10(root='./data', train=False, 
			download=True, transform=transform_test)
	
		kwargs = {'num_workers': 2, 'pin_memory': True} if args.cuda else {}
		trainloader = torch.utils.data.DataLoader(trainset, batch_size=
			args.batch_size, shuffle=True, **kwargs)
		testloader = torch.utils.data.DataLoader(testset, batch_size=
			args.batch_size, shuffle=False, **kwargs)
		self.trainloader = trainloader 
		self.testloader = testloader
	
	def getloader(self):
		return self.trainloader, self.testloader